What Data for This Category Looks Like
Daily documents for this category include process sheets, patterns, layout plans, cutting orders, first sample seals, process quality sheets, and packaging size allocation sheets. Data sources cover orders and size charts, CAD patterns, fabric and accessory inspection results, hanging system data, needle detector records, and customer sample seal information. Data updates are performed per order, per style, and per batch. Fields vary significantly across different document types. Process sheets include process parameters and fabric requirements. Layout plans mark cutting piece arrangement and fabric utilization rate. Packaging size allocation sheets specify size ratios and packaging rules. Some documents include exclusive unit information such as centimeters, kilograms, and piece counts.
Constraints on HTTP Interfaces and External Systems
This category has many document types with scattered fields. Interfaces must support batch import and parsing of multiple document types. Data updates occur at high frequency, so interfaces must adapt to high-frequency call scenarios and avoid triggering restrictions due to frequent calls. Data formats vary widely across different sources, so interfaces must support parsing logic for heterogeneous data and cannot directly use a unified template. Cutting piece-related data is irreversible, so interfaces must strictly verify the accuracy of incoming parameters to prevent incorrect data from entering the review process. When connecting across systems, real-time data from hanging systems and needle detectors must be synchronized, so interfaces must support context association across multiple data sources.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Authorization | Use a dedicated secret key generated by the platform, formatted as Bearer sk-xxxx | Ensure identity legitimacy for interface calls, and comply with the interface specifications of FastGPT v4.17.0 |
variables | Pass 10–15 custom fields, including order number, fabric batch, and size chart ID | Adapt to the multi-dimensional document association review requirements of this category |
responseData | Only return entries that failed review and their corresponding error messages | Reduce invalid data transmission and improve interface call efficiency |
| Maximum context length | 800–1200 characters | Cover core process and layout information for a single garment style |
| Request timeout | 30–60 seconds | Adapt to the processing duration of batch review for multiple documents |
| Parameter validation switch | Enable mandatory field validation | Prevent irreversible cutting piece data errors from entering the review process |
Three Common Configuration Mistakes
- Phenomenon: Custom context passed during interface calls is not correctly identified, and review results rely solely on the system's built-in historical conversation records. Cause: Custom context parameters are not configured in
variables, or the parameter format does not meet interface requirements. - Phenomenon: The interface returns status code 504 timeout, and the review process is interrupted. Cause: The set request timeout is too short, and does not adapt to the processing duration of batch review for multiple documents.
- Phenomenon: Incoming layout plan data is not correctly parsed, and the review result omits cutting piece supporting check items. Cause: Heterogeneous data format adaptation is not enabled in the configuration, and only a general document parsing template is used.
How to Verify Correct Configuration
- Invoke the test interface with the
variablesparameter containing the order number and fabric batch, and confirm the interface correctly receives and utilizes this parameter. - View the
responseDatareturned by the interface, and confirm only entries that failed review and their corresponding error messages are returned. - Simulate a high-frequency call scenario, and confirm the interface completes the response within the configured request timeout period.
- Pass document data with abnormal formats, and confirm the interface triggers parameter validation and returns clear error messages.
The values provided here are common starting points, and should be measured against the reader's own samples.